Simulation-optimization model for estimating hydraulic conductivity: a numerical case study of the Lu Dila hydropower station in China

Abstract

A simulation-optimization model (ADINA-MMRDE) has been developed using the commercial finite-element software ADINA coupled with an improved differential evolution algorithm (MMRDE) to estimate the hydraulic conductivity of the aquifer of the Lu Dila hydropower project in China. The ADINA-MMRDE model employed the sum of the weighted square difference between the simulated value and the observed value as the objective function. To evaluate the accuracy of the MMRDE, the ADINA software was also coupled with a classical differential evolution (DE) algorithm and particle swarm optimization (PSO). Before estimating the initial seepage field of the Lu Dila hydropower station, the performance of the ADINA-MMRDE model was first tested using a boundary-simplified model based on the initial seepage field model. The effects of different objective functions, measurement errors and population sizes on the performance of ADINA-MMRDE were investigated. Then the ADINA-MMRDE model was applied to the Lu Dila hydropower project by considering water levels in 20 boreholes. The results showed that the head calculated using the estimated parameters was very close to its observed value. The water levels of 13 monitoring boreholes were used for further confirmation of the parameters obtained by the inversion. The results revealed that the calculated values of the monitoring borehole water levels were generally well fitted to the measured values. This study demonstrated the effectiveness of the ADINA-MMRDE model for practical and complex parameter inversion tasks.